Pandas Profiling Report

Dataset statistics

Number of variables	22
Number of observations	95
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	16.5 KiB
Average record size in memory	177.3 B

Variable types

Numeric	12
Categorical	10

Alerts

`city` has constant value "Lahore"	Constant
`province_name` has constant value "Punjab"	Constant
`purpose` has constant value "For Sale"	Constant
`page_url` has a high cardinality: 95 distinct values	High cardinality
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`longitude` is highly correlated with `day`	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`day` is highly correlated with `longitude`	High correlation
`location_id` is highly correlated with `longitude` and 1 other fields	High correlation
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`latitude` is highly correlated with `longitude`	High correlation
`longitude` is highly correlated with `location_id` and 2 other fields	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`year` is highly correlated with `month`	High correlation
`month` is highly correlated with `year`	High correlation
`day` is highly correlated with `location_id` and 1 other fields	High correlation
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`longitude` is highly correlated with `day`	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`day` is highly correlated with `longitude`	High correlation
`locality` is highly correlated with `date_added` and 8 other fields	High correlation
`date_added` is highly correlated with `locality` and 5 other fields	High correlation
`area` is highly correlated with `locality` and 7 other fields	High correlation
`price_bin` is highly correlated with `locality` and 6 other fields	High correlation
`province_name` is highly correlated with `locality` and 8 other fields	High correlation
`page_url` is highly correlated with `locality` and 8 other fields	High correlation
`property_type` is highly correlated with `locality` and 6 other fields	High correlation
`location` is highly correlated with `locality` and 8 other fields	High correlation
`city` is highly correlated with `locality` and 8 other fields	High correlation
`purpose` is highly correlated with `locality` and 8 other fields	High correlation
`property_id` is highly correlated with `location_id` and 7 other fields	High correlation
`location_id` is highly correlated with `property_id` and 11 other fields	High correlation
`page_url` is highly correlated with `property_id` and 16 other fields	High correlation
`property_type` is highly correlated with `page_url` and 4 other fields	High correlation
`price` is highly correlated with `page_url` and 8 other fields	High correlation
`price_bin` is highly correlated with `location_id` and 8 other fields	High correlation
`location` is highly correlated with `property_id` and 16 other fields	High correlation
`locality` is highly correlated with `property_id` and 16 other fields	High correlation
`latitude` is highly correlated with `location_id` and 8 other fields	High correlation
`longitude` is highly correlated with `property_id` and 13 other fields	High correlation
`baths` is highly correlated with `location_id` and 12 other fields	High correlation
`area` is highly correlated with `property_id` and 16 other fields	High correlation
`area_marla` is highly correlated with `page_url` and 8 other fields	High correlation
`area_sqft` is highly correlated with `page_url` and 8 other fields	High correlation
`bedrooms` is highly correlated with `page_url` and 10 other fields	High correlation
`date_added` is highly correlated with `property_id` and 15 other fields	High correlation
`month` is highly correlated with `location_id` and 8 other fields	High correlation
`day` is highly correlated with `property_id` and 10 other fields	High correlation
`page_url` is uniformly distributed	Uniform
`property_id` has unique values	Unique
`page_url` has unique values	Unique
`baths` has 16 (16.8%) zeros	Zeros
`bedrooms` has 12 (12.6%) zeros	Zeros

Reproduction

Analysis started	2022-11-30 20:44:56.168028
Analysis finished	2022-11-30 20:45:44.022117
Duration	47.85 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

property_id
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	95
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3371864.116

Minimum	347795
Maximum	5019310
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	347795
5-th percentile	983065.7
Q1	2471475
median	3931998
Q3	4323660
95-th percentile	4698194.6
Maximum	5019310
Range	4671515
Interquartile range (IQR)	1852185

Descriptive statistics

Standard deviation	1176444.798
Coefficient of variation (CV)	0.3489004176
Kurtosis	-0.2625312105
Mean	3371864.116
Median Absolute Deviation (MAD)	625801
Skewness	-0.8067837016
Sum	320327091
Variance	1.384022363 × 10¹²
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
347795	1	1.1%
4017113	1	1.1%
4304977	1	1.1%
4249571	1	1.1%
4170552	1	1.1%
4159826	1	1.1%
4153988	1	1.1%
4111694	1	1.1%
4107715	1	1.1%
4100382	1	1.1%
Other values (85)	85	89.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
347795	1	1.1%
482892	1	1.1%
555962	1	1.1%
785289	1	1.1%
983065	1	1.1%
983066	1	1.1%
1286643	1	1.1%
1402784	1	1.1%
1606710	1	1.1%
1646880	1	1.1%

Value	Count	Frequency (%)
5019310	1	1.1%
4951451	1	1.1%
4940629	1	1.1%
4907568	1	1.1%
4747413	1	1.1%
4677101	1	1.1%
4570988	1	1.1%
4560911	1	1.1%
4557799	1	1.1%
4536854	1	1.1%

location_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	55
Distinct (%)	57.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5125.294737

Minimum	7
Maximum	10542
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	7
5-th percentile	73.2
Q1	1604
median	3847
Q3	9433
95-th percentile	9436
Maximum	10542
Range	10535
Interquartile range (IQR)	7829

Descriptive statistics

Standard deviation	3727.385516
Coefficient of variation (CV)	0.7272529108
Kurtosis	-1.646148423
Mean	5125.294737
Median Absolute Deviation (MAD)	3474
Skewness	0.09953995338
Sum	486903
Variance	13893402.78
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9435	9	9.5%
9434	6	6.3%
9433	6	6.3%
8172	5	5.3%
9436	4	4.2%
1784	3	3.2%
10542	3	3.2%
514	3	3.2%
9432	3	3.2%
3824	2	2.1%
Other values (45)	51	53.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
7	1	1.1%
8	2	2.1%
48	1	1.1%
69	1	1.1%
75	1	1.1%
154	2	2.1%
373	1	1.1%
377	1	1.1%
378	1	1.1%
496	1	1.1%

Value	Count	Frequency (%)
10542	3	3.2%
9747	1	1.1%
9436	4	4.2%
9435	9	9.5%
9434	6	6.3%
9433	6	6.3%
9432	3	3.2%
8444	1	1.1%
8425	1	1.1%
8172	5	5.3%

page_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	95
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1
https://www.zameen.com/Property/dha_defence_defence_raya_1_kanal_house_for_sale_at_facing_golf_park_dha_raya-4017113-8172-1.html	1
https://www.zameen.com/Property/dha_defence_dha_phase_4_house_for_sale_in_dha_phase_4-4304977-1446-1.html	1
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1
Other values (90)	90

Length

Max length	165
Median length	126
Mean length	124.8526316
Min length	88

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	95 ?
Unique (%)	100.0%

Sample

1st row	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html
2nd row	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html
3rd row	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html
4th row	https://www.zameen.com/Property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html
5th row	https://www.zameen.com/Property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html

Common Values

Value	Count	Frequency (%)
https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_defence_raya_1_kanal_house_for_sale_at_facing_golf_park_dha_raya-4017113-8172-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_dha_phase_4_house_for_sale_in_dha_phase_4-4304977-1446-1.html	1	1.1%
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1	1.1%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1	1.1%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_house_is_available_for_sale-4159826-3527-1.html	1	1.1%
https://www.zameen.com/Property/bahria_town_sector_c_bahria_town_tulip_block_10_marla_brand_new_house_in_sector_c_bahria_town_lahore-4153988-1789-1.html	1	1.1%
https://www.zameen.com/Property/dha_phase_5_dha_phase_5_block_a_1_kanal_beautiful_bungalow_house_for_sale-4111694-1598-1.html	1	1.1%
https://www.zameen.com/Property/dha_defence_dha_phase_6_1_kanal_brand_new_beautiful_bungalow_for_sale-4107715-1448-1.html	1	1.1%
https://www.zameen.com/Property/askari_10_askari_10_sector_f_17_marla_corner_brand_new_brig_house_available_for_sale-4100382-10542-1.html	1	1.1%
Other values (85)	85	89.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
https://www.zameen.com/property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.1%
https://www.zameen.com/property/askari_10_askari_10_sector_b_one_kanal_house_khalid_designed_main_boulevard_fully_renovated_available_for_sale-2471472-9433-1.html	1	1.1%
https://www.zameen.com/property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	1	1.1%
https://www.zameen.com/property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	1	1.1%
https://www.zameen.com/property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	1	1.1%
https://www.zameen.com/property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	1	1.1%
https://www.zameen.com/property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	1	1.1%
https://www.zameen.com/property/lahore_upper_mall_commercial_old_house_for_sale_upper_mall_lahore_excellent_location-1402784-514-1.html	1	1.1%
https://www.zameen.com/property/lahore_cavalry_ground_10_marla_house_is_available_for_sale-1606710-69-1.html	1	1.1%
https://www.zameen.com/property/bahria_town_sector_b_bahria_town_umar_block_double_storey_house_for_sale-1646880-1781-1.html	1	1.1%
Other values (85)	85	89.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

property_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

House	93
Flat	2

Length

Max length	5
Median length	5
Mean length	4.978947368
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	House
2nd row	House
3rd row	House
4th row	House
5th row	House

Common Values

Value	Count	Frequency (%)
House	93	97.9%
Flat	2	2.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
house	93	97.9%
flat	2	2.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	64
Distinct (%)	67.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	78244210.53

Minimum	3200000
Maximum	1250000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	3200000
5-th percentile	7190000
Q1	20750000
median	23500000
Q3	49750000
95-th percentile	366000000
Maximum	1250000000
Range	1246800000
Interquartile range (IQR)	29000000

Descriptive statistics

Standard deviation	193512583.4
Coefficient of variation (CV)	2.473187244
Kurtosis	25.98639693
Mean	78244210.53
Median Absolute Deviation (MAD)	11500000
Skewness	4.927041099
Sum	7433200000
Variance	3.744711994 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22500000	5	5.3%
23000000	5	5.3%
40000000	4	4.2%
23500000	4	4.2%
21500000	4	4.2%
35000000	3	3.2%
50000000	3	3.2%
22000000	3	3.2%
21000000	2	2.1%
3200000	2	2.1%
Other values (54)	60	63.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3200000	2	2.1%
5500000	2	2.1%
6000000	1	1.1%
7700000	1	1.1%
8000000	1	1.1%
9500000	1	1.1%
11800000	1	1.1%
12000000	2	2.1%
12500000	1	1.1%
13500000	1	1.1%

Value	Count	Frequency (%)
1250000000	1	1.1%
1200000000	1	1.1%
620000000	1	1.1%
480000000	1	1.1%
380000000	1	1.1%
360000000	1	1.1%
220000000	1	1.1%
180000000	1	1.1%
160000000	1	1.1%
87500000	1	1.1%

price_bin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Very High	41
High	40
Low	8
Medium	6

Length

Max length	9
Median length	4
Mean length	6.2
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Very High
2nd row	Very High
3rd row	Low
4th row	Very High
5th row	High

Common Values

Value	Count	Frequency (%)
Very High	41	43.2%
High	40	42.1%
Low	8	8.4%
Medium	6	6.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
high	81	59.6%
very	41	30.1%
low	8	5.9%
medium	6	4.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

location
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	28
Distinct (%)	29.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Askari	31
Gulberg	12
DHA Defence	10
Bahria Town	6
EME Society	5
Other values (23)	31

Length

Max length	36
Median length	7
Mean length	9.452631579
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	17.9%

Sample

1st row	Model Town
2nd row	Multan Road
3rd row	Eden
4th row	Gulberg
5th row	EME Society

Common Values

Value	Count	Frequency (%)
Askari	31	32.6%
Gulberg	12	12.6%
DHA Defence	10	10.5%
Bahria Town	6	6.3%
EME Society	5	5.3%
Allama Iqbal Town	3	3.2%
Upper Mall	3	3.2%
Paragon City	2	2.1%
Model Town	2	2.1%
Eden	2	2.1%
Other values (18)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
askari	31	20.8%
town	14	9.4%
gulberg	12	8.1%
dha	10	6.7%
defence	10	6.7%
society	8	5.4%
bahria	6	4.0%
eme	5	3.4%
housing	3	2.0%
allama	3	2.0%
Other values (32)	47	31.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

city
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Lahore	95

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Lahore
2nd row	Lahore
3rd row	Lahore
4th row	Lahore
5th row	Lahore

Common Values

Value	Count	Frequency (%)
Lahore	95	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
lahore	95	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

province_name
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Punjab	95

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Punjab
2nd row	Punjab
3rd row	Punjab
4th row	Punjab
5th row	Punjab

Common Values

Value	Count	Frequency (%)
Punjab	95	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
punjab	95	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

locality
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	28
Distinct (%)	29.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

Askari, Lahore, Punjab	31
Gulberg, Lahore, Punjab	12
DHA Defence, Lahore, Punjab	10
Bahria Town, Lahore, Punjab	6
EME Society, Lahore, Punjab	5
Other values (23)	31

Length

Max length	52
Median length	23
Mean length	25.45263158
Min length	19

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	17.9%

Sample

1st row	Model Town, Lahore, Punjab
2nd row	Multan Road, Lahore, Punjab
3rd row	Eden, Lahore, Punjab
4th row	Gulberg, Lahore, Punjab
5th row	EME Society, Lahore, Punjab

Common Values

Value	Count	Frequency (%)
Askari, Lahore, Punjab	31	32.6%
Gulberg, Lahore, Punjab	12	12.6%
DHA Defence, Lahore, Punjab	10	10.5%
Bahria Town, Lahore, Punjab	6	6.3%
EME Society, Lahore, Punjab	5	5.3%
Allama Iqbal Town, Lahore, Punjab	3	3.2%
Upper Mall, Lahore, Punjab	3	3.2%
Paragon City, Lahore, Punjab	2	2.1%
Model Town, Lahore, Punjab	2	2.1%
Eden, Lahore, Punjab	2	2.1%
Other values (18)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
punjab	95	28.0%
lahore	95	28.0%
askari	31	9.1%
town	14	4.1%
gulberg	12	3.5%
dha	10	2.9%
defence	10	2.9%
society	8	2.4%
bahria	6	1.8%
eme	5	1.5%
Other values (34)	53	15.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

latitude
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	57
Distinct (%)	60.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	31.50144782

Minimum	31.37108
Maximum	31.71727872
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	31.37108
5-th percentile	31.3795184
Q1	31.467691
median	31.522361
Q3	31.536068
95-th percentile	31.5562024
Maximum	31.71727872
Range	0.34619872
Interquartile range (IQR)	0.068377

Descriptive statistics

Standard deviation	0.05721863647
Coefficient of variation (CV)	0.001816381164
Kurtosis	1.596067507
Mean	31.50144782
Median Absolute Deviation (MAD)	0.019753
Skewness	-0.2242689936
Sum	2992.637543
Variance	0.003273972359
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31.533161	8	8.4%
31.537458	6	6.3%
31.469155	5	5.3%
31.53327	5	5.3%
31.536068	4	4.2%
31.537239	3	3.2%
31.374195	3	3.2%
31.533849	3	3.2%
31.542114	3	3.2%
31.518337	2	2.1%
Other values (47)	53	55.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
31.37108	1	1.1%
31.374195	3	3.2%
31.374414	1	1.1%
31.381706	1	1.1%
31.400096	1	1.1%
31.402513	1	1.1%
31.40537	1	1.1%
31.431593	1	1.1%
31.434668	1	1.1%
31.437744	2	2.1%

Value	Count	Frequency (%)
31.71727872	1	1.1%
31.597234	1	1.1%
31.590234	1	1.1%
31.57443055	1	1.1%
31.567912	1	1.1%
31.551184	1	1.1%
31.54913521	1	1.1%
31.543431	1	1.1%
31.542114	3	3.2%
31.539206	1	1.1%

longitude
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	58
Distinct (%)	61.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	74.3579356

Minimum	74.177749
Maximum	74.474513
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	74.177749
5-th percentile	74.191482
Q1	74.30294
median	74.385309
Q3	74.419481
95-th percentile	74.470553
Maximum	74.474513
Range	0.296764
Interquartile range (IQR)	0.116541

Descriptive statistics

Standard deviation	0.08313027288
Coefficient of variation (CV)	0.00111797446
Kurtosis	-0.5216629358
Mean	74.3579356
Median Absolute Deviation (MAD)	0.039761
Skewness	-0.7380302633
Sum	7064.003882
Variance	0.006910642268
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
74.419481	8	8.4%
74.413323	6	6.3%
74.470553	5	5.3%
74.41358	5	5.3%
74.408666	4	4.2%
74.420211	3	3.2%
74.191482	3	3.2%
74.409633	3	3.2%
74.355898	3	3.2%
74.348202	2	2.1%
Other values (48)	53	55.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
74.177749	1	1.1%
74.17998	1	1.1%
74.190316	1	1.1%
74.191482	3	3.2%
74.195294	1	1.1%
74.209685	2	2.1%
74.21349	2	2.1%
74.214005	1	1.1%
74.224648	1	1.1%
74.239683	1	1.1%

Value	Count	Frequency (%)
74.474513	1	1.1%
74.470553	5	5.3%
74.456184	1	1.1%
74.45599191	1	1.1%
74.451342	1	1.1%
74.445906	1	1.1%
74.44369633	1	1.1%
74.440012	1	1.1%
74.429569	1	1.1%
74.427137	1	1.1%

baths
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	8.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.326315789

Minimum	0
Maximum	8
Zeros	16
Zeros (%)	16.8%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.5
median	5
Q3	6
95-th percentile	7
Maximum	8
Range	8
Interquartile range (IQR)	2.5

Descriptive statistics

Standard deviation	2.308366399
Coefficient of variation (CV)	0.5335640095
Kurtosis	-0.3551702138
Mean	4.326315789
Median Absolute Deviation (MAD)	1
Skewness	-0.8328073281
Sum	411
Variance	5.328555431
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
5	27	28.4%
6	22	23.2%
0	16	16.8%
4	11	11.6%
7	8	8.4%
3	4	4.2%
2	4	4.2%
8	3	3.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	16	16.8%
2	4	4.2%
3	4	4.2%
4	11	11.6%
5	27	28.4%
6	22	23.2%
7	8	8.4%
8	3	3.2%

Value	Count	Frequency (%)
8	3	3.2%
7	8	8.4%
6	22	23.2%
5	27	28.4%
4	11	11.6%
3	4	4.2%
2	4	4.2%
0	16	16.8%

area
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

10 Marla	33
1 Kanal	21
2 Kanal	5
3 Marla	3
12 Marla	3
Other values (24)	30

Length

Max length	9
Median length	8
Mean length	7.673684211
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19 ?
Unique (%)	20.0%

Sample

1st row	6 Kanal
2nd row	1 Kanal
3rd row	9 Marla
4th row	1 Kanal
5th row	1 Kanal

Common Values

Value	Count	Frequency (%)
10 Marla	33	34.7%
1 Kanal	21	22.1%
2 Kanal	5	5.3%
3 Marla	3	3.2%
12 Marla	3	3.2%
17 Marla	3	3.2%
18 Marla	2	2.1%
2 Marla	2	2.1%
1.1 Kanal	2	2.1%
8 Kanal	2	2.1%
Other values (19)	19	20.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
marla	59	31.1%
kanal	36	18.9%
10	34	17.9%
1	21	11.1%
2	7	3.7%
3	3	1.6%
12	3	1.6%
17	3	1.6%
8	3	1.6%
6	2	1.1%
Other values (16)	19	10.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

area_marla
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.10947368

Minimum	2
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	2
5-th percentile	3
Q1	10
median	10
Q3	20
95-th percentile	101.8
Maximum	200
Range	198
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	34.37427624
Coefficient of variation (CV)	1.487453877
Kurtosis	12.65067532
Mean	23.10947368
Median Absolute Deviation (MAD)	6
Skewness	3.527115082
Sum	2195.4
Variance	1181.590867
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
10	33	34.7%
20	21	22.1%
40	5	5.3%
3	3	3.2%
12	3	3.2%
17	3	3.2%
18	2	2.1%
2	2	2.1%
22	2	2.1%
160	2	2.1%
Other values (19)	19	20.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	2	2.1%
2.5	1	1.1%
3	3	3.2%
4	1	1.1%
5	1	1.1%
5.5	1	1.1%
6	1	1.1%
7	1	1.1%
7.5	1	1.1%
8	1	1.1%

Value	Count	Frequency (%)
200	1	1.1%
160	2	2.1%
130	1	1.1%
120	1	1.1%
94	1	1.1%
80	1	1.1%
40	5	5.3%
24	1	1.1%
22	2	2.1%
20	21	22.1%

area_sqft
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	29
Distinct (%)	30.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6291.577053

Minimum	544.5
Maximum	54450.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	544.5
5-th percentile	816.75
Q1	2722.51
median	2722.51
Q3	5445.02
95-th percentile	27715.149
Maximum	54450.2
Range	53905.7
Interquartile range (IQR)	2722.51

Descriptive statistics

Standard deviation	9358.431098
Coefficient of variation (CV)	1.487453944
Kurtosis	12.65067546
Mean	6291.577053
Median Absolute Deviation (MAD)	1633.51
Skewness	3.527115069
Sum	597699.82
Variance	87580232.62
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
2722.51	33	34.7%
5445.02	21	22.1%
10890.04	5	5.3%
816.75	3	3.2%
3267.01	3	3.2%
4628.27	3	3.2%
4900.52	2	2.1%
544.5	2	2.1%
5989.52	2	2.1%
43560.16	2	2.1%
Other values (19)	19	20.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
544.5	2	2.1%
680.63	1	1.1%
816.75	3	3.2%
1089	1	1.1%
1361.25	1	1.1%
1497.38	1	1.1%
1633.51	1	1.1%
1905.76	1	1.1%
2041.88	1	1.1%
2178.01	1	1.1%

Value	Count	Frequency (%)
54450.2	1	1.1%
43560.16	2	2.1%
35392.63	1	1.1%
32670.12	1	1.1%
25591.59	1	1.1%
21780.08	1	1.1%
10890.04	5	5.3%
6534.02	1	1.1%
5989.52	2	2.1%
5445.02	21	22.1%

purpose
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

For Sale	95

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	For Sale
2nd row	For Sale
3rd row	For Sale
4th row	For Sale
5th row	For Sale

Common Values

Value	Count	Frequency (%)
For Sale	95	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
for	95	50.0%
sale	95	50.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

bedrooms
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	7.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.926315789

Minimum	0
Maximum	8
Zeros	12
Zeros (%)	12.6%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	4
Q3	5
95-th percentile	6
Maximum	8
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.823266331
Coefficient of variation (CV)	0.4643707812
Kurtosis	0.6562660982
Mean	3.926315789
Median Absolute Deviation (MAD)	1
Skewness	-0.8998456325
Sum	373
Variance	3.324300112
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
5	31	32.6%
4	28	29.5%
0	12	12.6%
3	10	10.5%
6	9	9.5%
2	3	3.2%
8	2	2.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12	12.6%
2	3	3.2%
3	10	10.5%
4	28	29.5%
5	31	32.6%
6	9	9.5%
8	2	2.1%

Value	Count	Frequency (%)
8	2	2.1%
6	9	9.5%
5	31	32.6%
4	28	29.5%
3	10	10.5%
2	3	3.2%
0	12	12.6%

date_added
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	22
Distinct (%)	23.2%
Missing	0
Missing (%)	0.0%
Memory size	888.0 B

06-18-2019	32
07/03/2019	10
05/03/2019	10
04/04/2019	7
06-25-2019	7
Other values (17)	29

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11 ?
Unique (%)	11.6%

Sample

1st row	07-17-2019
2nd row	10/06/2018
3rd row	07/03/2019
4th row	06/02/2019
5th row	07/03/2019

Common Values

Value	Count	Frequency (%)
06-18-2019	32	33.7%
07/03/2019	10	10.5%
05/03/2019	10	10.5%
04/04/2019	7	7.4%
06-25-2019	7	7.4%
04/03/2019	6	6.3%
06/11/2019	3	3.2%
02/03/2019	3	3.2%
12/05/2018	2	2.1%
06/02/2019	2	2.1%
Other values (12)	13	13.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
06-18-2019	32	33.7%
05/03/2019	10	10.5%
07/03/2019	10	10.5%
04/04/2019	7	7.4%
06-25-2019	7	7.4%
04/03/2019	6	6.3%
06/11/2019	3	3.2%
02/03/2019	3	3.2%
12/05/2018	2	2.1%
06/02/2019	2	2.1%
Other values (12)	13	13.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

year
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	2
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2018.957895

Minimum	2018
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	2018
5-th percentile	2019
Q1	2019
median	2019
Q3	2019
95-th percentile	2019
Maximum	2019
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2018947205
Coefficient of variation (CV)	9.999947053 × 10^-5
Kurtosis	19.8878751
Mean	2018.957895
Median Absolute Deviation (MAD)	0
Skewness	-4.633523198
Sum	191801
Variance	0.04076147816
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=2)

Value	Count	Frequency (%)
2019	91	95.8%
2018	4	4.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2018	4	4.2%
2019	91	95.8%

Value	Count	Frequency (%)
2019	91	95.8%
2018	4	4.2%

month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	10.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.673684211

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	6
Q3	6
95-th percentile	7
Maximum	12
Range	11
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.789104764
Coefficient of variation (CV)	0.3153338638
Kurtosis	3.805228521
Mean	5.673684211
Median Absolute Deviation (MAD)	0
Skewness	0.5405337936
Sum	539
Variance	3.200895857
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
6	48	50.5%
7	13	13.7%
4	13	13.7%
5	10	10.5%
2	4	4.2%
1	2	2.1%
12	2	2.1%
10	1	1.1%
3	1	1.1%
11	1	1.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2	2.1%
2	4	4.2%
3	1	1.1%
4	13	13.7%
5	10	10.5%
6	48	50.5%
7	13	13.7%
10	1	1.1%
11	1	1.1%
12	2	2.1%

Value	Count	Frequency (%)
12	2	2.1%
11	1	1.1%
10	1	1.1%
7	13	13.7%
6	48	50.5%
5	10	10.5%
4	13	13.7%
3	1	1.1%
2	4	4.2%
1	2	2.1%

day
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	14
Distinct (%)	14.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.37894737

Minimum	1
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	888.0 B

Quantile statistics

Minimum	1
5-th percentile	3
Q1	3
median	11
Q3	18
95-th percentile	25
Maximum	30
Range	29
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.435208567
Coefficient of variation (CV)	0.7412995503
Kurtosis	-1.315944037
Mean	11.37894737
Median Absolute Deviation (MAD)	7
Skewness	0.3412138252
Sum	1081
Variance	71.15274356
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
18	33	34.7%
3	29	30.5%
4	9	9.5%
25	7	7.4%
5	4	4.2%
11	3	3.2%
2	2	2.1%
30	2	2.1%
17	1	1.1%
6	1	1.1%
Other values (4)	4	4.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	1.1%
2	2	2.1%
3	29	30.5%
4	9	9.5%
5	4	4.2%
6	1	1.1%
10	1	1.1%
11	3	3.2%
12	1	1.1%
17	1	1.1%

Value	Count	Frequency (%)
30	2	2.1%
26	1	1.1%
25	7	7.4%
18	33	34.7%
17	1	1.1%
12	1	1.1%
11	3	3.2%
10	1	1.1%
6	1	1.1%
5	4	4.2%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day
0	347795	8	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	House	220000000	Very High	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.483869	74.325686	0	6 Kanal	120.0	32670.12	For Sale	0	07-17-2019	2019	7	17
1	482892	48	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html	House	40000000	Very High	Multan Road	Lahore	Punjab	Multan Road, Lahore, Punjab	31.431593	74.179980	5	1 Kanal	20.0	5445.02	For Sale	5	10/06/2018	2018	10	6
2	555962	75	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	House	9500000	Low	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.499348	74.416959	0	9 Marla	9.0	2450.26	For Sale	3	07/03/2019	2019	7	3
3	785289	3102	https://www.zameen.com/Property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	House	52000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.495909	74.350569	6	1 Kanal	20.0	5445.02	For Sale	5	06/02/2019	2019	6	2
4	983065	3749	https://www.zameen.com/Property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	House	32500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.439978	74.209685	0	1 Kanal	20.0	5445.02	For Sale	5	07/03/2019	2019	7	3
5	983066	3745	https://www.zameen.com/Property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	House	31500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.437744	74.213490	0	1 Kanal	20.0	5445.02	For Sale	6	07/03/2019	2019	7	3
6	1286643	3733	https://www.zameen.com/Property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	House	13500000	Medium	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.441113	74.239683	4	7.5 Marla	7.5	2041.88	For Sale	4	04/04/2019	2019	4	4
7	1402784	514	https://www.zameen.com/Property/lahore_upper_mall_commercial_old_house_for_sale_upper_mall_lahore_excellent_location-1402784-514-1.html	House	87500000	Very High	Upper Mall	Lahore	Punjab	Upper Mall, Lahore, Punjab	31.542114	74.355898	5	1.2 Kanal	24.0	6534.02	For Sale	4	06-30-2019	2019	6	30
8	1606710	69	https://www.zameen.com/Property/lahore_cavalry_ground_10_marla_house_is_available_for_sale-1606710-69-1.html	House	16500000	High	Cavalry Ground	Lahore	Punjab	Cavalry Ground, Lahore, Punjab	31.500557	74.367730	0	10 Marla	10.0	2722.51	For Sale	4	04/04/2019	2019	4	4
9	1646880	1781	https://www.zameen.com/Property/bahria_town_sector_b_bahria_town_umar_block_double_storey_house_for_sale-1646880-1781-1.html	House	18500000	High	Bahria Town	Lahore	Punjab	Bahria Town, Lahore, Punjab	31.381706	74.195294	0	10 Marla	10.0	2722.51	For Sale	0	07/04/2019	2019	7	4

Last rows

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day
85	4536854	3852	https://www.zameen.com/Property/gulberg_main_boulevard_gulberg_commercialized_piece_of_property_house_for_sale-4536854-3852-1.html	House	1200000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.519435	74.345548	0	8 Kanal	160.0	43560.16	For Sale	0	04/04/2019	2019	4	4
86	4557799	3850	https://www.zameen.com/Property/gulberg_mm_alam_road_shopping_paradise_of_lahore_house_for_sale-4557799-3850-1.html	House	380000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.510471	74.350526	0	2 Kanal	40.0	10890.04	For Sale	0	05/03/2019	2019	5	3
87	4560911	496	https://www.zameen.com/Property/mozang_mozang_chungi_al_qader_center_ground_floor_new_apartment_for_sale-4560911-496-1.html	Flat	3200000	Low	Mozang	Lahore	Punjab	Mozang, Lahore, Punjab	31.549135	74.315117	2	3 Marla	3.0	816.75	For Sale	2	07/03/2019	2019	7	3
88	4570988	1447	https://www.zameen.com/Property/dha_defence_dha_phase_5_original_faisal_rasool_brand_new_classical_bungalow-4570988-1447-1.html	House	59800000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.462493	74.409342	7	1 Kanal	20.0	5445.02	For Sale	6	05/03/2019	2019	5	3
89	4677101	8172	https://www.zameen.com/Property/dha_defence_defence_raya_dha_raya_2_kanal_facing_golf_course_fully_basement_house_for_sale-4677101-8172-1.html	House	66000000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.469155	74.470553	6	2 Kanal	40.0	10890.04	For Sale	6	06-25-2019	2019	6	25
90	4747413	154	https://www.zameen.com/Property/gulberg_zafar_ali_road_6_kanal_house_for_sale_on_zafar_ali_road_mall_road_upper_mall_lahore_excellent_location-4747413-154-1.html	House	360000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.538420	74.352357	7	10 Kanal	200.0	54450.20	For Sale	5	06-30-2019	2019	6	30
91	4907568	514	https://www.zameen.com/Property/lahore_upper_mall_4_kanal__house_for_sale_upper_mall_lahore-4907568-514-1.html	House	160000000	Very High	Upper Mall	Lahore	Punjab	Upper Mall, Lahore, Punjab	31.542114	74.355898	6	1 Kanal	20.0	5445.02	For Sale	5	01-18-2019	2019	1	18
92	4940629	8	https://www.zameen.com/Property/lahore_model_town_3_marla_house_for_sale-4940629-8-1.html	House	8000000	Low	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.473884	74.329080	3	3 Marla	3.0	816.75	For Sale	2	07/03/2019	2019	7	3
93	4951451	7	https://www.zameen.com/Property/lahore_gulberg_blue_zone_house_for_sale-4951451-7-1.html	House	480000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.522361	74.347172	0	4 Kanal	80.0	21780.08	For Sale	0	05/03/2019	2019	5	3
94	5019310	1534	https://www.zameen.com/Property/garden_town_garden_town_ahmed_block_purely_residential_apartments_for_sale-5019310-1534-1.html	Flat	22500000	Very High	Garden Town	Lahore	Punjab	Garden Town, Lahore, Punjab	31.507800	74.318733	0	7 Marla	7.0	1905.76	For Sale	0	04/03/2019	2019	4	3

Overview

Variables

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Pie chart

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Pie chart

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Pie chart

Most occurring characters

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Most occurring scripts

Most frequent character per script

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Most frequent character per block

Common Values

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Pie chart

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

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Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length